Computational scanning electron microscopy[1]} through rapid
artificial image modeling is gaining importance. It is a useful tool for evaluation of imaging and
metrology methods, since real SEMs or other charged-particle microscopes
cannot always provide repeatable images. For example, it is virtually impossible to obtain two real
SEM images that only differ in random noise. This is usually caused by many
perturbing factors like drift, sample charging, or electro-magnetic fields. The artificial
image generator is capable of modeling all important effects in a deterministic
way. One can a priori choose the drift function, the type
[2]}, [3]} and magnitude and type of noise, the
charged-particle-beam profile, etc. That being the case, computer generated artificial images may be
input to the imaging and metrological techniques and the results compared to the
chosen parameters, hence indicating the performance of given techniques. None of
these is possible with the real images, where these effects are present there,
but all are random and often even unknown.
